Constitutive Modeling of Brain Tissue: Current PerspectivesSource: Applied Mechanics Reviews:;2016:;volume( 068 ):;issue: 001::page 10801DOI: 10.1115/1.4032436Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Modeling the mechanical response of the brain has become increasingly important over the past decades. Although mechanical stimuli to the brain are small under physiological conditions, mechanics plays a significant role under pathological conditions including brain development, brain injury, and brain surgery. Well calibrated and validated constitutive models for brain tissue are essential to accurately simulate these phenomena. A variety of constitutive models have been proposed over the past three decades, but no general consensus on these models exists. Here, we provide a comprehensive and structured overview of stateoftheart modeling of the brain tissue. We categorize the different features of existing models into timeindependent, timedependent, and historydependent contributions. To model the timeindependent, elastic behavior of the brain tissue, most existing models adopt a hyperelastic approach. To model the timedependent response, most models either use a convolution integral approach or a multiplicative decomposition of the deformation gradient. We evaluate existing constitutive models by their physical motivation and their practical relevance. Our comparison suggests that the classical Ogden model is a wellsuited phenomenological model to characterize the timeindependent behavior of the brain tissue. However, no consensus exists for mechanistic, physicsbased models, neither for the timeindependent nor for the timedependent response. We anticipate that this review will provide useful guidelines for selecting the appropriate constitutive model for a specific application and for refining, calibrating, and validating future models that will help us to better understand the mechanical behavior of the human brain.
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| contributor author | de Rooij, Rijk | |
| contributor author | Kuhl, Ellen | |
| date accessioned | 2017-05-09T01:25:22Z | |
| date available | 2017-05-09T01:25:22Z | |
| date issued | 2016 | |
| identifier issn | 0003-6900 | |
| identifier other | amr_068_01_010801.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/160148 | |
| description abstract | Modeling the mechanical response of the brain has become increasingly important over the past decades. Although mechanical stimuli to the brain are small under physiological conditions, mechanics plays a significant role under pathological conditions including brain development, brain injury, and brain surgery. Well calibrated and validated constitutive models for brain tissue are essential to accurately simulate these phenomena. A variety of constitutive models have been proposed over the past three decades, but no general consensus on these models exists. Here, we provide a comprehensive and structured overview of stateoftheart modeling of the brain tissue. We categorize the different features of existing models into timeindependent, timedependent, and historydependent contributions. To model the timeindependent, elastic behavior of the brain tissue, most existing models adopt a hyperelastic approach. To model the timedependent response, most models either use a convolution integral approach or a multiplicative decomposition of the deformation gradient. We evaluate existing constitutive models by their physical motivation and their practical relevance. Our comparison suggests that the classical Ogden model is a wellsuited phenomenological model to characterize the timeindependent behavior of the brain tissue. However, no consensus exists for mechanistic, physicsbased models, neither for the timeindependent nor for the timedependent response. We anticipate that this review will provide useful guidelines for selecting the appropriate constitutive model for a specific application and for refining, calibrating, and validating future models that will help us to better understand the mechanical behavior of the human brain. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Constitutive Modeling of Brain Tissue: Current Perspectives | |
| type | Journal Paper | |
| journal volume | 68 | |
| journal issue | 1 | |
| journal title | Applied Mechanics Reviews | |
| identifier doi | 10.1115/1.4032436 | |
| journal fristpage | 10801 | |
| journal lastpage | 10801 | |
| identifier eissn | 0003-6900 | |
| tree | Applied Mechanics Reviews:;2016:;volume( 068 ):;issue: 001 | |
| contenttype | Fulltext |